activity
20192021
most citedUniversal Activation Function For Machine Learning

58 citations · 87 across the 4 of their papers we have counts for

collaborators

6 papers

eess.SP2021

Passive Indoor Localization with WiFi Fingerprints

Minh Tu Hoang, Brosnan Yuen, Kai Ren +5

This paper proposes passive WiFi indoor localization. Instead of using WiFi signals received by mobile devices as fingerprints, we use signals received by routers to locate the mob…

cs.LG2020★ 58 cited

Universal Activation Function For Machine Learning

Brosnan Yuen, Minh Tu Hoang, Xiaodai Dong +1

This article proposes a Universal Activation Function (UAF) that achieves near optimal performance in quantification, classification, and reinforcement learning (RL) problems. For…

cs.LG2020★ 13 cited

A CNN-LSTM Quantifier for Single Access Point CSI Indoor Localization

Minh Tu Hoang, Brosnan Yuen, Kai Ren +5

This paper proposes a combined network structure between convolutional neural network (CNN) and long-short term memory (LSTM) quantifier for WiFi fingerprinting indoor localization…

eess.SP2020★ 16 cited

Semi-Sequential Probabilistic Model For Indoor Localization Enhancement

Minh Tu Hoang, Brosnan Yuen, Xiaodai Dong +3

This paper proposes a semi-sequential probabilistic model (SSP) that applies an additional short term memory to enhance the performance of the probabilistic indoor localization. Th…

eess.SP2019

A Soft Range Limited K-Nearest Neighbours Algorithm for Indoor Localization Enhancement

Minh Tu Hoang, Yizhou Zhu, Brosnan Yuen +5

This paper proposes a soft range limited K nearest neighbours (SRL-KNN) localization fingerprinting algorithm. The conventional KNN determines the neighbours of a user by calculati…

eess.SP2019

Recurrent Neural Networks For Accurate RSSI Indoor Localization

Minh Tu Hoang, Brosnan Yuen, Xiaodai Dong +3

This paper proposes recurrent neuron networks (RNNs) for a fingerprinting indoor localization using WiFi. Instead of locating user's position one at a time as in the cases of conve…